Sr Engineer - Gen AI, FDE, Python

Key Responsibilities
Develop and maintain applications using Python, leveraging AI tools and frameworks wherever appropriate.
Build AI-powered applications using LLMs such as OpenAI GPT, Google Gemini, Anthropic Claude, or open-source models.
Design and implement GenAI solutions, including chatbots, document processing, knowledge assistants, and workflow automation.
Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector databases, and semantic search.
Build AI agents and multi-step workflows using frameworks such as LangChain and LangGraph.
Use AI coding assistants such as GitHub Copilot, Cursor, or similar tools to improve development productivity.
Integrate AI models and external services through REST APIs and Python-based backend services.
Develop APIs and backend applications using FastAPI, Flask, or similar frameworks.
Write clean, reusable, maintainable, and well-tested code, validating AI-generated code before production use.
Evaluate AI outputs for accuracy, reliability, latency, security, and cost.
Collaborate with product, engineering, and business teams to identify opportunities for AI-driven automation and innovation.
Follow best practices for application security, data privacy, version control, testing, and deployment.
Required Skills
2–5 years of experience in software development, primarily using Python.
Strong understanding of Python programming, OOP, data structures, exception handling, and debugging.
Hands-on experience with Generative AI, LLM APIs, and prompt engineering.
Experience integrating APIs and working with JSON, REST services, and third-party systems.
Understanding of RAG, embeddings, semantic search, and vector databases.
Familiarity with AI frameworks such as LangChain, LangGraph, or LlamaIndex.
Experience with FastAPI, Flask, or similar backend frameworks.
Working knowledge of Git, SQL, unit testing, and software development best practices.
Experience using AI-assisted coding tools to accelerate development and improve code quality.
Preferred
Skills Experience building AI agents, tool-calling workflows, and multi-agent systems.
Familiarity with vector databases such as FAISS, Chroma, Pinecone, or equivalent.
Exposure to Docker, CI/CD, and cloud platforms such as AWS, Azure, or GCP.
Knowledge of machine learning fundamentals and open-source models through Hugging Face.
Understanding of LLM evaluation, guardrails, hallucination mitigation, and responsible AI.
Experience with automated testing and AI-assisted software development workflows.

Work arrangement
No